21 Best + Free Machine Learning & Deep Learning Courses [2019]

Best Machine Learning Course

A team of 50+ global experts has done in-depth research to come up with this compilation of Best +Free Machine Learning and Deep Learning Course for 2019. All these courses are available online and will help you learn and excel at Machine Learning and Deep Learning. These are suitable for beginners, intermediate learners as well as experts. This compilation is reviewed and updated monthly. So far, 78,000+ students and professionals have benefited from it.


21 Best + Free Machine Learning and Deep Learning Courses [2019] [UPDATED]

1. Machine Learning Certification by Stanford University (Coursera)

Stanford Coursera CourseThis is the single highest rated course on Machine Learning on the entire internet. Created by Andrew Ng, Co-Founder of Coursera and Professor at Stanford University, the program has been taken up by more than 2,310,000 students & professionals globally, who have given it an average rating of a whopping 4.9 out of 5. One look at the testimonials and you will know why we so highly recommend it.

The topics covered in the course include supervised learning, best practices, and innovation in ML and AI, while you also get to encounter numerous case studies and applications among a host of other things. One of the best parts about the course is that you can enroll for a 7 day trial before going on to purchase the entire class. If you were to take our word for it, this is hands down the best program for the subject available online. You may also be interested in taking a look at a compilation of some of the best Machine Learning Certifications.


Key USPs-

– Understand parametric and non-parametric algorithms, clustering, dimensionality reduction, among other important topics.

– Gain best practices and advice from the instructor.

– Interact with your peers in a community of like-minded learners from all levels of experience.

– Real world based case studies give you the opportunity to understand how problems are solved on a daily basis.

– The flexible deadline allows you to learn as per your convenience.

– Learn to apply learning algorithms to build smart robots, understand text, audio, database mining.


Duration : Approx 55 hours, 7 hours per week

Rating : 4.9 out of 5

You can Sign up Here


Review : Truly an exceptional class. Not often will someone with a deep proficiency in a discipline have the time or incentive to share their insights and teach to others; this class is a rare exception, and given the vital importance of machine learning to the future, I have a great appreciation and debt to Andrew Ng. – Nicholas D



2. Deep Learning Certification by deeplearning.ai (Coursera)

deeplearning coursera courseOne of the most renowned instructors of Deep Learning, Andrew Ng brings to you this special course developed in association with Stanford Professors and nvidia|deep learning institute as industry partners. The trainer is the Co Founder of Coursera and has headed the Google Brain Project and Baidu AI group in the past.

In this program spread across 5 courses spanning few weeks, he will teach you about the foundations of Deep Learning, how to build neural networks and how to build machine learning projects. Most importantly, you will get to work on real time case studies around healthcare, music generation and natural language processing among other industry areas. More than 110,000 students have already enrolled for this program from all over the globe. Without a doubt, this is the Best Deep Learning Course out there. You can also have a look at some of the Best Data Science Courses.


Key USPs-

– Learn about convolutional networks, RNNs, BatchNorm, Dropout and more.

– Different techniques using which you can build models to solve real-life problems.

– Real-world case studies in fields such as healthcare, autonomous driving, sign language reading, music generation, and natural language processing are covered.

– Gain best practices and advice from the industry experts and leaders.

– Complete all the assessments and assignments as per your schedule to earn the specialization completion certification.


Duration: 3 months, 11 hours per week

Rating : 4.9 out of 5

You can Sign up Here 


Review : digitThis course formed a concrete background in building multi-layers neural network from scratch. The best advantage of this course is I was able to immediately apply the knowledge I gained into real world problem like humanoid navigation towards known targets. Illustration is great in terms of mathematical explanation and coding in a step by step walk through. – Waleed E



3. Machine Learning A-Z™: Hands-On Python & R In Data Science (Udemy)

Let us just begin by absorbing the fact that 411,800+ students have taken this course and it has an average rating of 4.5 out of 5. We consider this as one of the Best Machine Learning Course and it is developed by Kirill Eremenko, Data Scientist & Forex Systems Expert and Hadelin de Ponteves, Data Scientist.

This course will help you Master Machine Learning on Python and R, make accurate predictions, build a great intuition of many machine learning models, handle specific tools like reinforcement learning, NLP and Deep Learning. Most importantly it teaches you to choose the right model for each type of problem. Basic high school mathematics is all you are supposed to know to take up this course. With 40 hours of learning + 19 articles, we don’t know what else we should say to make you check this out. In case interested, you may also like to have a look at our compilation of Best Python Courses.


Key USPs –

– Great tutorial to get started with the topic with little or no prior experience.

– Explore complex topics such as natural language processing, reinforcement learning, deep learning among many others.

– Tons of practical exercises and quizzes to measure your grasp on the concepts covered in the lectures.

– Detailed instructions are provided to install the required software and tools.

– As a bonus, this training contains both Python and R code template that can be downloaded and used in projects.


Duration : 41 hours

Rating :4.5 out of 5.

You can Sign up here


Review – Machine Learning A-Z is a great introduction to ML. A big tour through a lot of algorithms making the student more familiar with scikit-learn and few other packages. The theoretical explanation is elementary, so are the practical examples. ML-az is a right course for a beginner to get the motivation to dive deep in ML. From here you can choose where to go and, therefore, master it! In short, very introductory, no-brainer, wide coverage. A good way to start. -Denis Mariano



4. Machine Learning Nanodegree Program (Udacity)

This Udacity Nanodegree Program that will help you gain the must-have skills for all aspiring data analysts and data scientists. Explore the end to end process of investigating data through a machine learning lens. Learn to extract and identify useful features that can be used to represent your data in the best form. In addition to this, you will also go over some of the most important ML algorithms and evaluate their performance.


Key USPs-

– Interactive quizzes allow you to brush up the topics covered.

– Join the student support community to exchange ideas and clarify doubts.

– The self-paced schedules allow you to learn as per your convenience.

– The content has been created in association with Kaggle and AWS

– You will learn about supervised learning, deep learning, unsupervised learning among a host of other topics

– You also get a one on one mentor, personal career coaching along with access to student community


Duration: 3 months

Rating: 4.6 out of 5

You can Sign up Here 



5. Machine Learning Data Science Course from Harvard University (edX)

Harvard Online Courses

This Harvard University professional certification program uses motivating case studies, asks specific questions and shows you how to answer them by analyzing huge amounts of data. Throughout the classes, you will learn the R programming language, statistical concepts, and data analysis techniques simultaneously. The case studies covered include Trends in World Health and Economics, US Crime Rates, the Financial Crisis of 2007-2008, election Forecasting, Building a baseball Team and Movie Recommendation Systems. The professor of this course is Rafael Irizarry, Professor of Biostatistics at Harvard University.


Key USPs –

– Cover the fundamental R programming skills.

– Explore statistical concepts such as probability, inference, and modeling and apply them in practice.

– Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr.

– Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio.

– Implement machine learning algorithms and gain in-depth knowledge of this area with real-life case studies.


Duration: 9 courses, 2 to 8 weeks per course, 2 to 4 hours per week, per course

Rating : 4.7 out of 5

You can Sign up Here



6. Mathematics for Machine Learning by Imperial College London (Coursera)

It is safe to say that machine learning is literally everywhere today. Many of us take numerous courses to learn the various concepts in these topics but unfortunately, one of the crucial parts of this field is often overlooked. This specialization aims to bridge that gap and helps you to build a solid foundation in the underlying mathematics, its intuitive understanding and use it in the context of machine learning and data science. Start with Linear Algebra and Multivariate Calculus before moving on to more complex concepts. By the end of the classes, you will have a strong mathematical footing to take more advanced lessons in ML and become a professional.


Key USPs-

– Fundamental concepts show you how to use them on huge pools of information.

– The lectures include a detailed explanation of how to get started with the graded assignments.

– The third course is of intermediate level and requires basic Python and numpy knowledge.

– Optimize fitting functions to get good fits to data.

– The doubts are clarified to provide a clear understanding of mathematics and apply it in necessary problems.


Duration: 2 months, 12 hours per week

Rating: 4.6 out of 5

You can Sign up Here 


Review : This course brilliantly delivered on each of its intended learning objectives in an engaging and non-threatening way – I would encourage anyone interested in this topic, regardless of their background. The course instructors are excellent, and the forum discussions are extremely helpful if/when you are ever stuck. – Daniel G



7. Deep Learning Course by IBM (edX)

With this domain gone mainstream in recent years, IBM brings this certification to you to help you explore the nooks and crannies of this subject and jump-start a career in this field. A series of courses delve into the concepts and applications of deep learning along with the various forms of neural networks for both supervised and unsupervised learning. Build models and algorithms by using different libraries such as TensorFlow, PyTorch, and Keras. Leverage GPU accelerated hardware for object recognization, image and video processing, and natural language processing at a large scale. Work on hands-on labs, assignments, and real-world projects and end the classes by completing a capstone project that can be showcased in your resume. You may want to check out more Deep Learning Certifications.


Key USPs –

– Build, train and deploy different types of Deep Architectures, including convolutional and recurrent networks and autoencoders.

– There are practical assignments and quizzes that will help you measure your grasp on the knowledge acquired.

– Get equipped with the skills required to become successful AI practitioners and start a career in this field.


Duration: 5 courses, 5 to 6 weeks per course

Rating : 4.6 out of 5

You can Sign up Here 



8. Machine Learning – Artificial Intelligence by Columbia University (edX)

This micromasters program designed by Columbia University brings you a rigorous, advanced, professional and graduate-level foundational class in AI and its subfields like machine learning, neural networks and more. With a total of 4 courses in this program go over the important concepts of this topic none by one. Gain a solid foundation of the guiding principles of AI and apply the knowledge of machine learning to real-world challenges and applications. Along with this, you will also learn to design neural networks and utilize them to work on relevant problems. By the end of the program, you will have adequate practical knowledge to enhance your portfolio, apply to relevant job profiles or go freelance. Do remember to check out the best AI Courses as compiled by experts on our website.


Key USPs-

– Apply the concepts of machine learning to real-life challenges and applications.

– Thorough instructions are provided for configuring and navigating through the required software.

– Working on designing and harnessing the capabilities of the neural network.

– The program is divided into 4 courses along with relevant examples and demonstrations.

– Apply the knowledge gained in these lectures in an array of fields such as robotics, vision and physical simulations.


Duration: 4 courses, 12 weeks per course, 8 to 10 hours per week, per course

Rating: 4.5 out of 5

You can Sign up Here 




9. Advanced Machine Learning Course by HSE (Coursera)

This certification course has been developed by a team of 21 lecturers, professors and researchers; and it is an advanced level journey into the world of ML. Only those with basic or intermediate knowledge around the subject should enroll for this one. You will be taught about natural language understanding, reinforcement learning, computer vision, and Bayesian methods. Some of the trainers for this program include Pavel Shvechikov, Researcher at HSE and Sberbank AI Lab, Anna Kozlova, Team Lead; Evgeny Sokolov, Senior Lecturer; Alexey Artemov, Senior Lecturer and Sergey Yudin, Analyst-developer among multiple other trainers. If you have a strong understanding of the machine learning concepts and are proficient in solving relevant challenges then this specialization will help you to go a notch higher.


Key USPs-

– Get introduced to advanced topics such as deep learning, reinforcement learning, natural language processing, computer vision and more.

– The lessons are designed concisely which helps you to learn new skills in a short amount of time as well as enhance your portfolio.

– Assignments give you an opportunity to implement the knowledge covered in the lessons.

– Work on projects and learn about the experiences of top CERN scientists and Kaggle machine learning practitioners.


Duration : Flexible Schedule

Rating : 4.6 out of 5

You can Sign up Here


Review : This course is one of the most difficult I have seen but at the same time it is very well structured. Lectures are understandable, one just need some support from other materials to understand a whole content, at least for me. I struggled a bit with a final project but in general, I enjoyed it a lot, I looked forward to it each week, it was challenging and achievable. I recommend it. – Vratislav H



10. Python for Everybody by University of Michigan (Coursera)

University of MichiganThis specialization will introduce you to the foundational programming concepts including data structures, networked application program interfaces, and databases using Python. After the completion of all the core concepts, you will get the opportunity to work on a final project and design and create your own applications for data retrieval, processing, and visualization.


Key USPs-

– Perfect for learners with little or no basic programming experience.

– Implement the concepts covered in the lessons by writing your first Python program and experimenting with the different techniques.

– The lectures are designed in a fun and interactive manner which makes it engaging and intriguing.

– The program is divided into a series of 5 courses with an increasing level of difficulty.

– Create applications for data retrieval and processing.

– Understand the basics of SQL and database design.


Duration: 3 months, 11 hours per week

Rating: 4.8 out of 5

You can Sign up Here


Review : I love the teaching style of Dr. Severance!! I’ve tried so many other tutorials online but his class is by far my favorite. He helps cement connections by use of metaphors and visual aids and as a student who has traditionally favored subjects such as language arts, it has been invaluable to my learning experience!! – Lorilyn M



11. Free Deep Learning Course in Python (DataCamp)

If you are more of a hands-on learner and prefer to learn by doing then this program by DataCamp will certainly appeal to you. Gain the practical knowledge that teaches you to work on deep learning using Keras 2.0 which is the latest version of a cutting edge library in this area. Commence with the fundamental terminology and understand how to optimize the predictions generated by neural networks. Following this, you will build models for both regression and classifications and improve them by analyzing the loose points.


Key USPs-

– Understand the significance of the techniques used in this area.

– Build simple neural networks and generate predictions.

– Use important methods such as backward propagation.

– Guidance is provided to equip you with the tools required to build the models.


Duration: 4 hours

Rating: 4.4 out of 5

You can Sign up Here 



12. Python for Data Science and Machine Learning Bootcamp (Udemy)

Use this powerful and in-demand language to analyze data, create beautiful visualizations and utilize powerful machine learning algorithms. Some of the crucial topics covered include solving complex tasks with pandas data frames, linear regression, decision trees, neural nets, web scrapping, interactive visualizations and support vector machines. With over 200,000 students and glowing ratings, this certification is a crowd favorite.  This program has been designed by well renowned online instructor Jose Portilla, a BS and MS in Engineering from Santa Clara University.


Key USPs-

– Learn to use Pandas for data analysis.

– Use Spark for Big Data Analysis, SciKit Learn for machine learning tasks along with many other tools.

– The relaxed and interactive teaching style of the instructor creates a great learning environment.

– 149 Lectures + 10 Articles + 4 Downloadable resources + Full lifetime access


Duration: 22.5 hours

Rating: 4.6 out of 5

You can Sign up here


Review : Woah! This course covered a ton of material – data analysis, data visualization, and machine learning (including deep learning)! It was a pleasure to take this course. It was definitely worth it for me, even though I have already taken several machine learning courses in the past. 🙂 – John Rattz



13. Deep Learning A-Z™: Hands-On Artificial Neural Networks (Udemy)

Created by Kirill Eremenko and Hadelin de Ponteves, this is one of the Best Deep Learning Course that you will find out there. It will help you understand the intuition behind Artificial Neural Networks, Recurrent Neural Networks, Self Organizing Maps, Boltzmann Machines, Auto Encoders and teach you how to apply them. The thing with AI is, that the more it advances, the more complex become the problems it needs to solve.

This course is carefully designed to give you the full experience of working in this technology from scratch. The lectures don’t only cover the techniques of solutions to the problem but it also describes the importance of the techniques and how it actually makes a difference. Along with the classes, you will get the chance to work on exciting projects with real-world datasets. With over 120,000 students, this training is certainly a crowd favorite.


Key USPs –

– These lectures can be taken by individuals with any level of experience in this field.

– Understand the intuition behind the recurrent and convolutional network, Boltzmann machines and apply them in practice.

– Write the codes from scratch in every practical tutorial with guidance from the instructor.

– All the codes are available for download and can be used in projects.

– Work on six real-life challenges with updated datasets.

– Learn to work with some of the most popular open source tools such as Tensorflow, Pytorch among others.

– 187 Lectures + Full lifetime access + 32 Articles


Duration: 22.5 hours

Rating: 4.5 out of 5

You can Sign up here


Review : This is the third course i concluded with Kirill and Hadelin, the experience is always very pleasant with a lot of content and things to learn. This specific course brings lavish recommendation articles and texts so you can go deeper into the more complex supervised and unsupervised algorithms. For me, always an A+. – Leandro Coriolano



14. Machine Learning Certification by University of Washington (Coursera)

University of WashingtonThis is an advanced level certification and participants should come with basic or intermediate level understanding of the subject before enrolling. Taught by Emily Fox and Carlos Guestrin, both Amazon Professors of Machine Learning, it is a comprehensive course spread over the period of multiple weeks. Key areas covered in the course include Clustering, Information Retrieval, Prediction, Classification among all other relevant topics.


Duration : Approx 6 months

Rating : 4.8 out of 5

You can Sign up Here


Review – Great course! I love the instructors and the thoroughly designed structure of their course. The effort they put into this course certainly shines through every video!



15. Free Machine Learning Courses (edX)

edX brings together a host of courses on machine learning from a variety of colleges across the globe. You can choose to study Data Science from Harvard, Artificial Intelligence from Columbia, Python Data Science from IBM or Data Science from Microsoft among a host of other courses. Most of these programs are free to audit, and you only need to pay if you wish to enroll for a certificate. With timings ranging from a few weeks to a few months, there’s something for everyone in these courses.


Key USPs –

– Free courses for those not wanting to shell out big bucks to learn machine learning

– Explore the various topics of machine learning and artificial intelligence and gain a strong understanding

– Learn with an abundant amount of tips and tricks from the instructors

– Build complex data models, explore data classifications, regression and clustering and more.

– Numerous courses to choose from covering a range of topics from AI to Machine Learning, Deep Learning and more

– Top professors from leading universities teach you


Duration: Self-paced

Rating: 4.6 out of 5

You can Sign up Here 



16. Free Machine Learning & AI Courses (fast.ai)

This is one of the top platforms that provide courses on topics that come under artificial intelligence and is created with the aim to teach the masses about AI and how to get started in the field. All the content is covered from scratch and focuses on learning by doing. There are a series of choices available for both beginners and experienced learners. So if you are serious about getting started in this area then the easiest way is to click on the first lecture.


Key USPs-

– Each and every concept is covered with screenshots and hands-on examples.

– Complete guidance is provided to perform the configuration to get started with the lectures.

– Join the forum to communicate with peers and practitioners and help each other through the learning experience.

– Use the fast.ai library and train models.

– All the courses on this platform are available for free.


Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here 



17. Complete Guide to TensorFlow for Deep Learning Tutorial with Python (Udemy)

Jose Portilla has another highly rated and recommended course online, and this one’s about Deep Learning. Targeted towards fans of Python, this training will cover a variety of topics including Neural Network, TensorFlow, Artificial Neural Networks, AutoEncoders Reinforcement Learning and more.

In trying to make you a true Deep Learning Guru, Jose will teach you how to build your neural network from scratch with Python, using TensorFlow for a variety of applications such as Image Classification with Convolutional Neural Networks, Time Series Analysis with Recurrent Neural Networks and solving Unsupervised Learning Problems with AutoEncoders.


Complete Guide to TensorFlow for Deep Learning with Python Review : Excellent

Rating : 4.6 out of 5

You can Sign up Here


Review : Excellent course. Portilla sets a pedagogical curve. Responsive Q&A, and reliable and regularly updated course materials are made available. Good foundation to a broad array of well-established and cutting-edge topics, and many useful external resources provided. – Jack Rasmus-Vorrath



18. Data Science and Machine Learning Tutorial with Python – Hands On (Udemy)

Frank Kane, the author of this course spent 9 years at Amazon and IMDb, developing and managing the technology that automatically that powers movie and product recommendations which influence millions of people around the world. With that kind of experience, no wonder even Ph.D students like Robert Crabbs are all praises about the program.

In technical terms, this machine learning tutorial will help you extract meaning from large data sets using a wide variety of data science, data mining and machine learning techniques using Python. Along with that, you will get to apply your learning as well.


Data Science and Machine Learning with Python Review : Very Good

Rating : 4.5 out of 5

You can Sign up here


Review : Clear an simple explanation. Excellent real world examples that are easy to digest an open up exciting possibilities when thought through further. Well done! Thanks so much, Frank! – Raymond Neo



19. Data Science and Machine Learning Bootcamp with R

If all the previous courses concentrated on Python, this one is about R. With over 100 lectures  and detailed code notebooks, this is one of the most comprehensive course for machine learning and data science. One of the best parts about the course is its instructor. Jose Marcial Portilla, has a BS and MS in Engineering from Santa Clara University and has been working as a professional instructor and trainer for Data Science & programming for many years now.

With his rich experience, you’ll get to learn how to program with R, to create amazing data visualizations, and use Machine Learning with R. You will also learn Programming with R, Advanced R Features, Using R Data Frames to solve complex tasks, using R to handle Excel Files, Web scraping with R, Connecting R to SQL and more. With very good reviews praising the program’s technical aspects, we recommend this one for R fans.


Data Science and Machine Learning Bootcamp with R Review : Excellent

Rating : 4.7 out of 5

You can Sign up here


Really good course to build up expertise in R. Machine learning explanation is less but adequate. Points you in the right direction if you want to explore mathematics behind the concepts. 4.5 stars for an excellent course in R and an introduction to ML concepts. – Nitin Sharma



20. Machine Learning Courses for Beginners (LinkedIn Learning – Lynda)

With over 25 courses, this set of training covers almost every possible knowledge that could be required to get started with machine learning and put your skills to practical use. There are lectures based on various platforms such as Amazon Web Services, Google Cloud Platform and you can take your pick as per your convenience. Get a basic understanding of artificial intelligence and machine learning concepts with the essential training and take lessons such as NLP with Python to get hands-on with projects. By the end of the classes, you will be well equipped with the skills covered in the videos and ready to take on more challenging specializations.


Duration: Self-paced

Rating : 4.6 out of 5

You can Sign up Here 



21. Scala and Spark for Big Data and Machine Learning Tutorial

If Python or R aren’t your cup of tea, this training helps you learn Scala and Spark for Big Data and Machine Learning. It will act as a crash course in Scala Programming, Spark and offer a Big Data Ecosystem overview using Spark’s MLlib for Machine Learning.

All that is required to sign up for this training is basic math skills and some programming knowledge in any language. The course will help you learn machine learning online and comes with full projects helping you analyze financial data and use machine learning.


Scala and Spark for Big Data and Machine Learning Review : Very Good

Rating : 4.4 out of 5

Scala and Spark fans, you can Sign up here


So that was our take on the Best Machine Learning Courses and Deep Learning Courses for 2019 which we hope puts you in the fast lane and help you earn those extra dollars. Since all these courses and training are online, they are available at minimal costs and can be accessed from any country across the globe. These days everybody needs to skill up to scale up, and we wish you the best in your journey. If you liked this article enough, do share it with your friends and well and also sign up for our newsletter to keep up with similar awesome insights once every fortnight.

Wishing you the best with your career! Cheers! Team Digital Defynd.